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CMS Conference Reports

ეძებე 4,869 ჩანაწერები:
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უკანასკნელი დამატებები:
2023-09-26
14:26
Evaluating Performance Portability with the CMS Heterogeneous Pixel Reconstruction code / CMS Collaboration
In the past years the landscape of tools for expressing parallel algorithms in a portable way across various compute accelerators has continued to evolve significantly. There are many technologies on the market that provide portability between CPU, GPUs from several vendors, and in some cases even FPGAs. [...]
CMS-CR-2023-127.- Geneva : CERN, 2023 - 9 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
Adoption of a token-based authentication model for the CMS Submission Infrastructure. / Mascheroni, Marco (UC, San Diego) /CMS Collaboration
The CMS Submission Infrastructure (SI) is the main computing resource provisioning system for CMS workloads. A number of HTCondor pools are employed to manage this infrastructure, which aggregates geographically distributed resources from the WLCG and other providers. [...]
CMS-CR-2023-170.- Geneva : CERN, 2023 - 7 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
The integration of heterogeneous resources in the CMS Submission Infrastructure for the LHC Run 3 and beyond / Perez-Calero Yzquierdo, Antonio Maria (Madrid, CIEMAT) ; Mascheroni, Marco (UC, San Diego) ; Kizinevic, Edita (CERN) ; Khan, Farrukh Aftab (Fermilab) ; Kim, Hyunwoo (Fermilab) ; Acosta Flechas, Maria (Fermilab) ; Tsipinakis, Nikos (CERN) ; Haleem, Saqib (Quaid-i-Azam U.) /CMS Collaboration
While the computing landscape supporting LHC experiments is currently dominated by x86 processors at WLCG sites, this configuration will evolve in the coming years. LHC collaborations will be increasingly employing HPC and Cloud facilities to process the vast amounts of data expected during the LHC Run 3 and the future HL-LHC phase. [...]
CMS-CR-2023-169.- Geneva : CERN, 2023 - 9 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
HPC resources for CMS offline computing: an integration and scalability challenge for the Submission Infrastructure / Perez-Calero Yzquierdo, Antonio Maria (Madrid, CIEMAT) ; Mascheroni, Marco (UC, San Diego) ; Kizinevic, Edita (CERN) ; Khan, Farrukh Aftab (Fermilab) ; Kim, Hyunwoo (Fermilab) ; Acosta Flechas, Maria (Fermilab) ; Tsipinakis, Nikos (CERN) ; Haleem, Saqib (Quaid-i-Azam U.) /CMS Collaboration
The computing resource needs of LHC experiments are expected to continue growing significantly during the Run 3 and into the HL-LHC era. The landscape of available resources will also evolve, as HPC and Cloud resources will provide a comparable, or even dominant, fraction of the total compute capacity. [...]
CMS-CR-2023-168.- Geneva : CERN, 2023 - 9 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
A method for inferring signal strength modifiers by conditional invertible neural networks / Farkas, Mate Zoltan (Aachen, Tech. Hochsch.) ; Diekmann, Svenja (Aachen, Tech. Hochsch.) ; Eich, Niclas Steve (Aachen, Tech. Hochsch.) ; Erdmann, Martin (Aachen, Tech. Hochsch.) /CMS Collaboration
The continuous growth in model complexity in high-energy physics (HEP) collider experiments demands increasingly time-consuming model fits. We show first results on the application of conditional invertible networks (cINNs) to this challenge. [...]
CMS-CR-2023-162.- Geneva : CERN, 2023 - 8 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
End-to-end deep learning inference with CMSSW via ONNX using Docker / Chudasama, Ruchi (Alabama U.) /CMS Collaboration
Deep learning techniques have been proven to provide excellent performance for a variety of high energy physics applications, such as particle identification, event reconstruction and trigger operations. Recently, we developed an end-to-end deep learning approach to identify various particles using low-level detector information from high energy collisions. [...]
CMS-CR-2023-161.- Geneva : CERN, 2023 - 9 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
Search for new physics with long-lived and unconventional signatures in CMS / Diaz, Daniel Cipriano (UC, San Diego) /CMS Collaboration
A selection of new results from the CMS detector is presented. These results focus on searches for long lived particles (LLPs) and were produced with Run~2 data. [...]
CMS-CR-2023-158.- Geneva : CERN, 2023 - 7 p. Fulltext: PDF;
In : The 31th International Symposium on Lepton-Photon Interactions at High Energies (Lepton Photon 2023), Melbourne, Victoria, Australia, 17 - 21 Jul 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:59
Line Segment Tracking in the High-luminosity LHC / Chang, Philip (Florida U.) /CMS Collaboration
The Large Hadron Collider (LHC) will be upgraded to High-luminosity LHC, increasing the number of simultaneous proton-proton collisions (pile-up, PU) by several-folds. The harsher PU conditions lead to exponentially increasing combinatorics in charged-particle tracking, placing a large demand on the computing resources. [...]
CMS-CR-2023-157.- Geneva : CERN, 2023 - 8 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:58
Boosted Higgs boson measurements at CMS / Asawatangtrakuldee, Chayanit (Chulalongkorn U.) /CMS Collaboration
Searches for the high transverse momentum ($p_{T}$) or boosted of the Higgs boson via gluon-gluon fusion and vector boson fusion productions are presented, where the Higgs boson decays to either a pair of bottom quarks or $\tau$ leptons. The results are based on proton-proton collision data collected by the CMS experiment at the LHC at a center-of-mass energy of 13 TeV. [...]
CMS-CR-2023-155.- Geneva : CERN, 2023 - 7 p. Fulltext: PDF;
In : 2023 European Physical Society Conference on High Energy Physics (EPS-HEP2023), Hamburg, Germany, 20 - 25 Aug 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-25
17:58
Overview of the HL-LHC Upgrade for the CMS Level-1 Trigger / Savard, Claire (Colorado U.) /CMS Collaboration
The High-Luminosity LHC will open an unprecedented window on the weak-scale nature of the universe, providing high-precision measurements of the standard model as well as searches for new physics beyond the standard model. Such precision measurements and searches require information-rich datasets with a statistical power that matches the high-luminosity provided by the Phase-2 upgrade of the LHC. [...]
CMS-CR-2023-154.- Geneva : CERN, 2023 - 8 p. Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

დეტალური ჩანაწერი - მსგავსი ჩანაწერები